Adapting to the light environment, plants have evolved several photoreceptors, of which the phytochromes are specialized in perceiving the red and far-red light region of the spectrum. Although phytochrome was first discovered in plants, the phytochrome species are present in several organisms, including bacteria. The mechanisms by which phytochromes transduce light signals to downstream components are most well studied in plants. Upon light activation, phytochromes translocate from the cytoplasm into nucleus and regulate the gene expression network through interaction with nuclear transcription factors. The phytochrome molecule can be divided into two major domains: the N-terminal moiety, which is responsible for the light perception, and the C-terminal moiety. Although the C-terminal moiety was though to be involved in signal transduction, it has recently been shown that the N-terminal moiety has a role not only in the light perception, but also in light signal transfer to the downstream network. However, no signaling motifs have been found in the N-terminal moiety. In this study, we analyzed intragenic mutations derived from a genetic screen and found a cluster of residues necessary for signal transduction in a small region neighboring the light-sensing chromophore moiety on the three-dimensional structure. This is an important step towards understanding how a major plant photoreceptor, phytochrome, intramolecularly processes the light signal to trigger diverse physiological responses.

Biochemical networks, consisting of biomolecules such as proteins and DNA that chemically and physically interact with one another, are the processing devices of life. Metabolic networks allow living cells to process food, while signal transduction pathways and gene regulatory networks allow living cells to process information. Experiments in recent years have demonstrated that these networks are often very “noisy”: the protein concentrations often fluctuate strongly. However, how this “biochemical noise” affects the growth rate or fitness of an organism is poorly understood. We present here a mathematical model that makes it possible to predict quantitatively how protein concentration fluctuations affect the growth rate of a cell population. The model predicts that fluctuations reduce the growth rate when evolution has tuned the average protein concentration to the level that maximizes the growth rate; however, when the average concentration deviates sufficiently from the optimal one, fluctuations can actually enhance the growth rate. Our analysis also predicts that the optimal design of a regulatory network is determined by the trade-off between the cost of synthesizing the proteins that constitute the regulatory network and the benefit of reducing the fluctuations in the network that it controls. Our predictions can be tested in wild-type and synthetic networks.

The timescale of the evolution of plant viruses is an enigma, and even its order of magnitude is unknown. This critical issue is addressed here by calculating the age of plant viruses. An accurate estimate of the age of Rice yellow mottle virus (RYMV) was obtained by statistical analysis of a set of dated sequences. The age of RYMV provides a reliable calibration of related viruses, applying recently developed relaxed molecular clock models. It was found that RYMV diversified approximately 200 years ago, and that inter-specific diversification ranged from 500 years to 9,000 years. Altogether, plant virus diversification has spanned the history of agriculture from the Neolithic age to the present. This suggests that the Neolithic was a period of epidemiological transition for plant virus diseases, as already proposed for infectious human diseases. Intrinsically, it is for the same reason: increased contacts between hosts, pathogens, and vectors. This is consistent with the view that RNA viruses have a recent origin, and that humans have become the world’s greatest evolutionary force.

Dengue viruses (DENVs) circulate in nature as a population of 4 distinct types, each with multiple genotypes and variants, and represent an increasing global public health issue with no prophylactic and therapeutic formulations currently available. Viral genomes contain sites that are evolutionarily stable and therefore highly conserved, presumably because changes in these sites have deleterious effects on viral fitness and survival. The identification and characterization of the historical dynamics of these sites in DENV have relevance to several applications such as diagnosis and drug and vaccine development. In this study, we have identified sequence fragments that were conserved across the majority of available DENV sequences, analyzed their historical dynamics, and evaluated their relevance as candidate vaccine targets, using various bioinformatics-based methods and immune assay in human leukocyte antigen (HLA) transgenic mice. This approach provides a framework for large-scale and systematic analysis of other human pathogens.

To identify mechanisms that regulate mammalian longevity, we have quantified the expression parallels of a number of long-lived mice that show delayed aging and DNA repair mutants that age and die prematurely. Unexpectedly, we found significant, genome-wide similarities and a widespread overlap of over-represented biological processes in the transcriptomes of these disparate mouse strains. Subsequent analysis revealed that similar responses are triggered constitutively in a number of organs in aged mice. Thus, both intrinsic and environmental stressors (e.g., aging, genome instability, or food shortage) induce survival responses aimed at overcoming crisis and extending lifespan. Such survival responses are likely to allow assessment of biological age as well as provide valuable targets for therapies aimed at health-span extension.

Characterizing the functional variation in an individual is an important step towards the era of personalized medicine. Protein-coding exons are thought to be especially enriched in functional variation. In 2007, we published the genome sequence of J. Craig Venter. Here we analyze the genetic variation of J. Craig Venter’s exome, focusing on variation in the coding portion of genes, which is thought to contribute significantly to a person’s physical make-up. We survey ~12,500 nonsilent coding variants and, by applying multiple bioinformatic approaches, we reduce the number of potential phenotypic variants by ~8-fold. Our analysis provides a snapshot of the current state of personalized genomics. We find that <1% of variants are linked to any known phenotypes; this demonstrates the dearth of scientific knowledge for phenotype-genotype associations. However, ~80% of an individual's nonsynonymous variants are commonly found in the human population and, because phenotypic associations to common variants will be elucidated via genome-wide association studies over the next few years, the capability to interpret personalized genomes will expand and evolve. As sequencing of individual genomes becomes more prevalent, the bioinformatic approaches we present in this study can be used as a paradigm to pursue the study of protein-coding variants for the genomes of many individuals.

Changes in gene expression have been suggested to play a major role in mammalian evolution. In eukaryotes, gene expression is primarily controlled by sites, such as transcription factor binding sites (TFBSs), located in the noncoding region of the genome. The majority of these TFBSs remain unannotated, however, because they are typically short, degenerate, and laborious to identify experimentally. As a result, the effects of mutations in TFBSs on organism fitness remain poorly understood. We collected a dataset of TFBSs derived from the experimental biology literature and recent high-throughput studies to estimate the proportions of new mutations in TFBSs that have strongly deleterious and strongly beneficial effects upon organism fitness. We find that a relatively high proportion of new mutations in TFBSs are strongly deleterious, although it appears that relatively few are adaptive. We also demonstrate that the fraction of strongly deleterious regulatory mutations is correlated with the breadth of expression of the regulated gene. Thus, ubiquitously expressed genes are likely to experience fewer deleterious regulatory mutations than those expressed in a small number of tissues.

The goal of the present work is to develop a biologically constrained three-dimensional model of the brain microstructure. This is an important task because the brain’s three-dimensional microstructure cannot be directly visualized, yet a knowledge of its structure is essential for understanding normal brain functioning. We first explore the shortcomings of the conventional modeling approach that treats brain tissue as a two-phase material. These models either do not preserve realistic features of brain tissue or preserve these properties while overestimating the brain’s effective diffusivity, an average measure of the underlying microstructure. We thus developed a biologically constrained two-phase model that, upon analysis, achieves a lower diffusion coefficient than other constrained models yet proves to not have a low enough diffusion coefficient to be a valid representation of the brain microstructure. We then show that if the extracellular matrix is incorporated as a third phase in this model, then the reduction in the diffusion coefficient achieved allows the proposed model to be a valid representation of the brain microstructure. Using this model, we can test the impact that microstructural changes have on the transport of nutrients and signaling molecules in the brain.

Until recently, the highly pathogenic avian influenza (HPAI) viruses responsible for high mortality in some domestic poultry were considered not to have a wild bird reservoir, but to emerge in domestic poultry populations from low pathogenic viruses perpetuated in wild waterbirds. The rapid spread of H5N1 HPAI virus in 2005-2006, with concurrent outbreaks reported in both domestic and wild birds over Asia, Europe, and Africa, has raised concerns about the potential role of migratory birds in the epidemiology of the HPAI infection. Wild birds were sampled in Africa and tested by molecular and virological methods in an attempt to trace the circulation of HPAI viruses. In addition, some of these wild birds were equipped with satellite transmitters to track their local and migratory movements in relation to the potential spread of avian diseases. Avian influenza viruses (H5N2) were detected in wild waterfowl in Nigeria, and were subsequently characterized as highly pathogenic by molecular sequencing (HPAI viral genotype). Movements of one infected bird tracked by satellite telemetry revealed that it survived infection by an HP viral genotype. This result constitutes a rare finding of infection by an AIV with an HPAI viral genotype in healthy wild birds.